A Data-drive Approach for Robust Cockpit Crew Training Scheduling

This work addresses the cockpit crew training scheduling problem. The objective is to produce a robust cockpit crew training schedule, including the assignment of trainees, instructors and simulators. To attain this objective, we propose a scheduling framework composed of four modules: a Training Scheduling & Assignment Model (TS&AM),...

Efficient reduction techniques for a large-scale Transmission Expansion Planning problem

The aim of Transmission Expansion Planning (TEP) studies is to decide which, where, and when new grid elements should be built in order to minimize the total system cost. The lumpiness of the investment decisions, together with the large size of the problem, make the problem very hard to solve. Consequently, methods should be put in place to...

Scheduling Non-Urgent Patient Transportation While Maximizing Emergency Coverage

Many ambulance providers operate both advanced life support (ALS) and basic life support (BLS) ambulances. Typically, only an ALS ambulance can respond to an emergency call, whereas non-urgent patient transportation requests can be served by either an ALS or a BLS ambulance. The total capacity of BLS ambulances is usually not enough to...

Exact formulation and comparison between the user optimum and system optimum solution for routing privately owned automated vehicles

The possibility of having driverless cars on the streets seems to be more real than ever. In this paper, we focus on developing exact methods that can determine the effects of privately owned automated vehicles (AVs) and how switching to those vehicles is going to change mobility in urban environments. The considered problem determines the...